Evidence map›Paper›PMID 33481258›Full record

ArticleHealth services research2021

Accounting for uncertainty in policy decision making: Improving access to pediatric dental care.

Stewart Curry, Nicoleta Serban

Abstract read
In one paragraph

Article in Health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Dental care access for children in the United States.Journal of public health dentistry · 2024
    Article
  2. Article
  3. Evaluating access to pediatric oral health care in the southeastern states.Journal of the American Dental Association (1939) · 2022
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Stewart CurrySchool of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
Nicoleta SerbanSchool of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.ORCID 0000-0002-5813-7435

Funding

Access to Preventive Dental Care for Children in the United StatesR01DE028283 · NIDCR · GEORGIA INSTITUTE OF TECHNOLOGY · PI SERBAN, NICOLETA · 2018 to 2021
$1.5M
NIDCR NIH HHS R01 DE028283
6 · The paper itself

Abstract

objectiveTo introduce a statistical inference framework for policy decision making on access to pediatric dental care. DATA SOURCES: Secondary data were collected for the state of Colorado for year 2019. STUDY

designThe access model was an optimization model, matching the demand (patients) and supply (providers) of dental care. Sampling distributions of model inputs were specified using hierarchical Bayesian models, with hyperparameters informed by prior information derived from multiple data sources. Simultaneous inference was applied to identify areas for access improvement. The model was applied to make inference on the pediatric dental care in Colorado, accounting for financial access, differentiated into public (Medicaid and CHIP), private (commercial and out-of-pocket), and without financial access. DATA COLLECTION/EXTRACTION

methodsMultiple data sources informed the access measurement approach including: 2017 American Community Survey, 2019 Colorado Dental Board, and 2019 National Provider Plan and Enumeration System, 2019 InsureKidsNow.gov among others. PRINCIPAL

findingsThe median access measure (travel distance) was greater than the Colorado access standards in 16.9% and 65.1% of census tracts for children with private financial access and publicly insured, respectively. Accounting for uncertainty (confidence level 99%), these percentages decreased to 14.6% and 25.6%, respectively, with mostly suburban and rural tracts failing to meet the standards. The median disparity for Medicaid and CHIP versus private financial access was greater than 5 miles in 84.5% and 81.6% of census tracts, respectively. Accounting for uncertainty (confidence level 99%), these percentages declined to 19.5% and 10.5%, respectively, with significant disparities around the metropolitan areas.

conclusionsWhile many communities failed to meet access standards, when accounting for uncertainty, most urban ones did not fail. Disparities in spatial access between publicly and privately insured were most acute in urban communities. Medicaid insured experienced higher disparities than CHIP insured; those differences were not identified when not accounting for uncertainty.

Indexed as

Policy MakingUncertaintyAdolescentBayes TheoremChildChild, PreschoolDental CareFemaleHealth Services AccessibilityHealth Services Needs and DemandHumansInfantMaleMedical AssistanceResidence CharacteristicsSocioeconomic FactorsBayesian modeldental carehealth care accessstatistical inferenceuncertainty quantification

Identifiers

PMID33481258
PMCPMC8186474

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.